Abstract
In this work, we summarize some of the recent statistical, spectral, and network methods for the financial time series analysis. The main focus is first on spectral analysis of the eigenvalues and eigenvector of the cross-correlations between the different financial commodities, and second, the threshold networks derived from the cross-correlation matrix. We used an information theoretic measures called eigenvector localization defined as the “eigenvector entropy” to derive the community structure and interactions between the financial commodities in a system. Lastly, network analysis is performed on the system which shows how the interaction within the system changes with time. In this article, we present and compare the results of two different systems: (1) global financial indices of 31 countries and (2) foreign exchange rates of 21 different currencies using a rolling window method.
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Acknowledgements
ND thanks Department of Science and Technology (DST), India (SERB-DST No- EMR/2016/006536) for financial support, and PB acknowledges NU research grant, Naresuan University, Thailand for financial support.
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Bhadola, P., Deo, N. (2019). Spectral and Network Method in Financial Time Series Analysis: A Study on Stock and Currency Market. In: Chakrabarti, A., Pichl, L., Kaizoji, T. (eds) Network Theory and Agent-Based Modeling in Economics and Finance. Springer, Singapore. https://doi.org/10.1007/978-981-13-8319-9_17
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DOI: https://doi.org/10.1007/978-981-13-8319-9_17
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